Uppsala universitet

Kalman Smoothing for Irregular Pilot Patterns;
A Case Study for Predictor Antennas in TDD Systems.

Rikke Apelfröjd , Uppsala University and Ericsson Research
Joachim Björsell , Uppsala University,
Mikael Sternad , Uppsala University, and
Dinh-Thuy Phan-Huy , Orange Labs, Paris, France.

IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) , Bologna, Italy, September 2018.

This paper received a PIMRC2018 Best Paper Award.

Paper In Pdf

Presentation slides

For future large-scale multi-antenna systems, channel orthogonal downlink pilots are not feasible due to extensive overhead requirements. Instead, channel reciprocity can be utilized in time division duplex (TDD) systems so that the downlink channel estimates can be based on pilots transmitted during the uplink. User mobility affects the reciprocity and makes the channel state information outdated for high velocities and/or long downlink subframe durations. Channel extrapolation, e.g. through Kalman prediction, can reduce the problem but is also limited by high velocities and long downlink subframes.

An alternative solution has been proposed where channel predictions are made with the help of an extra antenna, e.g. on the roof of a car, so called predictor antenna, with the primary objective to measure the channel at a position that is later encountered by the rearward antenna(s). The predictor antenna is not directly limited by high velocities and allows the channel in the downlinks to be interpolated rather than extrapolated.

One remaining challenge here is to obtain a good interpolation of the uplink channel estimate, since a sequence of uplink reference signals (pilots) will be interrupted by downlink subframes. We here evaluate a Kalman smoothing estimate of the downlink channels and compare it to a cubic spline interpolation. These results are also compared to results where uplink channels are estimated through Kalman filters and predictors.

Results are based on measured channels and show that with Kalman smoothing, predictor antennas can enable accurate channel estimates for a longer downlink period at vehicular velocities. The gaps in the uplink pilot stream, due to downlink subframes, can have durations that correspond to a vehicle movement of up to 0.75 carrier wavelengths in space, for Rayleigh-like non-line-of-sight fading.

Related publications:

PhD Thesis by Rikke Apelfröjd, April 2018, in which the submitted version of this paper represents Paper V.

Paper at IEEE ICC 2017 that provides the statistical estimate of the prediction accuracy when using predictor antennas.

Paper at IEEE WCNC 2012, Original proposal for using "Predictor antennas" for long-range prediction of fast fading for moving relays.

WSA 2018 paper verifying with measurements that predictor antennas enable precise precoding for massive MIMO antennas in non-line-of sight.

Conference paper at EUCAP 2014 presenting compensation of antenna coupling.

IEEE Intelligent Transportation Systems Magazine 2015: Making 5G adaptive antennas work for very fast moving vehicles.

Paper at Globecom 2016 5G Workshop on the gain by predictor antennas in terms of spectral efficiency and power efficiency when serving connected vehicles by 5G Massive MIMO antennas.

Channel Estimation and Prediction for MIMO OFDM Systems.
PhD Thesis by Danel Aronsson, Uppsala University 2011.

Prediction of Mobile Radio Channels.
PhD Thesis by Torbjörn Ekman, Uppsala University 2002.

| Main entry in list of publications | 4G and 5G wireless research | Channel prediction |
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